An interactive framework for video surveillance event detection and modeling

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Abstract

We present a framework for high-level event detection in video streams based on a novel temporal extension of relational algebra. With the help of intuitive and interactive graphical user interfaces, a user can have a look at the different layers of our system to gain insights into the inner workings of the system, as well as create new events on the fly and track their processing through the system. As a proof-of-concept we have predefined events on three video surveillance data sets, but we also plan to run a demo with a live video stream generated by a local webcam.

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Persia, F., Bettini, F., & Helmer, S. (2017). An interactive framework for video surveillance event detection and modeling. In International Conference on Information and Knowledge Management, Proceedings (Vol. Part F131841, pp. 2515–2518). Association for Computing Machinery. https://doi.org/10.1145/3132847.3133164

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